Pruning Analysis for the Position Specific Posterior Lattices for Spoken Document Search

J. Silva, C. Chelba, and Alex Acero

Abstract

The paper presents the Position Specific Posterior Lattice

(PSPL), a novel lossy representation of automatic speech

recognition lattices that naturally lends itself to efficient indexing

and subsequent relevance ranking of spoken documents.

Two pruning techniques for generating word lattices are

explored in this framework, where experiments performed on

a collection of lecture recordings — MIT iCampus database

— show that the spoken document ranking accuracy was improved

by 20%—in the mean average precision sense—relative

over the commonly used baseline of indexing the 1-best

output from an automatic speech recognizer (ASR).

Details

Publication typeInproceedings
Published inProc. of the Int. Conf. on Acoustics, Speech, and Signal Processing
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